Research On The Product Service System Redisign Methods Based On User Experience

Product Service System(PSS),characterized by user-center and personalization,should be redesigned during operation to adapt to the changes of user requirements and market.User experience(UE)is critical decision information for PSS redesign.With the development of information collection wireless communication,the cost of collecting UE data decreases,which enable the collection and usage of UE.The UE data includes user behavior data,feedback data,environment data etc.UE data reflect user's direct feelings from the aspects of sense,emotion,thinking,behavior.Thus,the enterprises expcet to enhance market competition by extract decision information from UE data for PSS redesign.This research aims to provide theoretical methods and tools for enterpises who are planning to redesign PSS based on UE.There are two difficult issues in PSS redesign based on UE.Firstly,UE data will be generated during each operation stages with different forms,such as user online reviews,sensor signal and questionaires.Each data plays different roles in different design stages.How to extract useful decision information is critical for PSS redesign.Secondly,UE is difficult to model because of the subjectivity and time-varing characteristics.Designers' decisions depend greatly on experience,which makes the design information fuzzy.Thus,there will be a great deal of fuzzy uncertainties and random uncertainties co-occurrence in PSS redesign.Therefore,two scientific problems are proposed.The first one is how to obtain UE and translate it into PSS redesign conceptions.The second one is how to deal with fuzzy uncertainties and random uncertainties simultaneously.Four Key technologies will be researched: UE factor extraction based on interval number principal component analysis and questionnaire development technique,redesign module recognization based on different UE data,module parameters optimization based on fuzzy random nunlinear programming model,and information content calculation for hybrid uncertain evaluation criteria.Detailed works are listed as follows:(1)A UE model for PSS redesign is conctructed by extracting UE factors and weighting them.The users of PSS are usually companies or some teams,which are complicated compared with single user.The characteristics of PSS users are analyzed seriously,according to which questionares of UE for different users are designed separately.Considering the fuzziness of user's answer of UE questionares,interval number principal component analysis is employed to determine the factors of UE.In PSS conceptual redesign,the improved importance of of each UE factor should be calculated except for basic importance.The improved importance is influenced by planned improved amount,possibility index and salespoint.The planned improved amount is obtained from viewpoint of users by analyzing online review.The possibility index is calculated with balanced scorecard.And importance-performance anlysis is adopted to analyze the relationship between basic importance and performace,thus to calculate the salespoint.(2)A method of redesign module identification is proposed based on FMEA and UE.RPN(Risk Priority Number)is introduced to measuer the relationship between PSS module and UE.The severity,occurance and detectivity are all gathered to calculated the RPN.Occurance is modeled as random variable,while detectivity is modeled as fuzzy variable.Thus the fuzzy random simulation technique is adopted to solve the product of a random variable and a fuzzy variable.(3)A fuzzy nonlinear programming model is constructed to optimize the module parameters based on UE process data.Due to the professionalism of module parameters,it is difficult for users to experience the differences of different values.Thus,the UE process data is introduced to modeling the relationship between UE and module parameters.The UE process data evolved in this paper could be classified into product/service operation data,user feedback data and environment data.Prouduct/service operation data and the environment data are used to determine the importance of design parameters and which design parameters should be optimized.The user feedback data is used to determine the index of design parameters.The fuzzy nonlinear programming model is transformed into two models,fuzzy chance constrained expect value programming model and chance constrained programming model.Fuzzy random simulation technique and GA are used to solve these two models.(4)A PSS conception evaluating method under hybrid uncertain environment is proposed.The evaluation criteria system is constructed considering economic,environemtal,and social aspect.To solve fuzzy uncertainty and random uncertainty simultaneously,Information Axiom is adopted to evaluate the PSS conceptions.The system range and design range are modeled as random variable and fuzzy variable respectively for a hybrid uncertain criteria.The Information Content of a hybrid uncertain criteria evolve integration whose up bound and low bound are fuzzy numbers.Thus,fuzzy simulation technique is adopted to solve this problem.In order to express the risk appetite of decision makers,the credibility theory is introduced to construct two Information Content models for the hybrid uncertain critiria.The expect value model reflect the neutralizing attitude of risk,while the credibility model could reflect different risk appitite by setting different confidence level.GA is designed to solve the credibility model.Above all,this research proposes a thorough framework for PSS redesign,provides technologies and approaches for UE modelling,redesign module recognization,design parameters opertimizaiton and concet evaluation,lays a foundation for the following research of this topic.Finally,a case study of crawler crane PSS redesign is performed to illustrate the feasibility and effectivity of the above methods.